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Intelligent alarm handling
A method of automatimj the knowledge acquisition task for process plant expert systems. (D. R. Bedford and P. H. F. T. Buck - UK) Following on the problem of knowledge acquisition discussed previously, this paper described a new, alternative method for knowledge acquisition which utilises the highly-structured nature of the problem domain in the process. Essentially, the knowledge is captured, in this approach, from a model-based diagnostic system. The required knowledge is defined in plant-related terms, and can be obtained from an examination of the plant's structure. The claimed advantages of this method include: •
Systems may be produced rapidly- even for large plants. • The experts are provided with a system to extend and improve without being involved in the tedious process of knowledge acquisition. • The knowledge is captured in a structured manner, allowing ultimately easier maintenance of the knowledge-base. • Essentially, the accuracy of the knowledge-base is improved.
Intelligent alarm handling. (0. Ogard and E. Woods - Norway) It has long been recognised that a critical part of any real-time control system must lie in the handling of alarms. This particular paper addressed the functional structure of an intelligent alarm system, in which the alarm structure is regarded as a joint cognitive system in which the operator's need for information at different abstraction levels is taken into account. The alarm system is divided into various levels, backed by a high-level decision-support system. The top level is further decomposed into modules for handling alarms, and diagnosing their causes. The paper discussed how this might be achieved, using a newly-developed method based on the parsing of incoming event sequences. The parsing process is itself based on a formal grammar which describes causal relationships on the plant. Parameter-passing and calls to the AI system are used to promulgate additional constraints and build up parse trees. The overall structure described provides, essentially, levels of alarm-handling, one being the actual alarm-handling system which presents alarms to operators, and the other providing decision support, to handle diagnostic problems.
Knowledge-supported generation of control room pictures. (P. Elzer, H. W. Borchers, C. Weisand and K. Zinser West Germany) This paper pointed out that it has been widely demonstrated that knowledge-based techniques and modern computer graphical methods have much potential for improving the operator interface in large process-control situations. Such improvements can be optimised by well-designed presentation techniques as well as by offering knowledge-based failure detection, prediction and explanation. In order to investigate the potential of a number of these new techniques, and to test their application, a joint project was started under one of the EEC initiatives - the ESPRIT programme involving a variety of academic and industrial bodies. Within the framework of this project, a prototype has been developed in order to gain experience with various forms of interface, and its applicability has been tested, together with user-acceptability. This prototype consists essentially of the following components: a software simulator of a conventional plant, running on conventional hardware and coupled to an AI workstation; a knowledge-base containing a hierarchy of over-view pictures of the total power plant, each offering a different level of detail; and models of various expert systems for applications such as failure-situation assessment, the manipulation of presented pictures according to a given situation, or providing additional, detailed advice to the operator. The current experience obtained with this project was discussed. In particular, this presentation focused on the development of a prototype of an intelligent graphical editor to support the new form of control-room pictures required, and it was demonstrated that a higher degree of support for the designer can be achieved by a combination of AI techniques and modern graphics. -
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Knowledge-based fuzzy motion control of autonomous vehicles. (C. J. Harris and A. B. R e a d - UK) From one of the leading European laboratories active in the development of intelligent mobile land-based autonomous vehicles, came this critical paper from Chris Harris and his colleagues. They showed how such a land-based autonomous vehicle can be modelled as a hierarchy of multi-sensor data fusion, scene recognition, path planning, navigation and motion control. The
Eng. Appli. of AI, 1988, Vol. 1, September
213
Systems may be produced rapidly- even for large plants. • The experts are provided with a system to extend and improve without being involved in the tedious process of knowledge acquisition. • The knowledge is captured in a structured manner, allowing ultimately easier maintenance of the knowledge-base. • Essentially, the accuracy of the knowledge-base is improved.
Intelligent alarm handling. (0. Ogard and E. Woods - Norway) It has long been recognised that a critical part of any real-time control system must lie in the handling of alarms. This particular paper addressed the functional structure of an intelligent alarm system, in which the alarm structure is regarded as a joint cognitive system in which the operator's need for information at different abstraction levels is taken into account. The alarm system is divided into various levels, backed by a high-level decision-support system. The top level is further decomposed into modules for handling alarms, and diagnosing their causes. The paper discussed how this might be achieved, using a newly-developed method based on the parsing of incoming event sequences. The parsing process is itself based on a formal grammar which describes causal relationships on the plant. Parameter-passing and calls to the AI system are used to promulgate additional constraints and build up parse trees. The overall structure described provides, essentially, levels of alarm-handling, one being the actual alarm-handling system which presents alarms to operators, and the other providing decision support, to handle diagnostic problems.
Knowledge-supported generation of control room pictures. (P. Elzer, H. W. Borchers, C. Weisand and K. Zinser West Germany) This paper pointed out that it has been widely demonstrated that knowledge-based techniques and modern computer graphical methods have much potential for improving the operator interface in large process-control situations. Such improvements can be optimised by well-designed presentation techniques as well as by offering knowledge-based failure detection, prediction and explanation. In order to investigate the potential of a number of these new techniques, and to test their application, a joint project was started under one of the EEC initiatives - the ESPRIT programme involving a variety of academic and industrial bodies. Within the framework of this project, a prototype has been developed in order to gain experience with various forms of interface, and its applicability has been tested, together with user-acceptability. This prototype consists essentially of the following components: a software simulator of a conventional plant, running on conventional hardware and coupled to an AI workstation; a knowledge-base containing a hierarchy of over-view pictures of the total power plant, each offering a different level of detail; and models of various expert systems for applications such as failure-situation assessment, the manipulation of presented pictures according to a given situation, or providing additional, detailed advice to the operator. The current experience obtained with this project was discussed. In particular, this presentation focused on the development of a prototype of an intelligent graphical editor to support the new form of control-room pictures required, and it was demonstrated that a higher degree of support for the designer can be achieved by a combination of AI techniques and modern graphics. -
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Knowledge-based fuzzy motion control of autonomous vehicles. (C. J. Harris and A. B. R e a d - UK) From one of the leading European laboratories active in the development of intelligent mobile land-based autonomous vehicles, came this critical paper from Chris Harris and his colleagues. They showed how such a land-based autonomous vehicle can be modelled as a hierarchy of multi-sensor data fusion, scene recognition, path planning, navigation and motion control. The
Eng. Appli. of AI, 1988, Vol. 1, September
213